在 Azure ML 中自定义命名实体识别模型 [英] Customizing the Named Entity Recogntition model in Azure ML

问题描述

我们可以使用单独的训练数据集在 Azure ML Studio 中自定义命名实体识别 (NER) 模型吗?我想做的是从文本中找出非英文名称.(训练数据集包括将用于训练的名称集)

Can we customize the Named Entity Recognition (NER) model in Azure ML Studio with a separate training dataset? What I want to do is to find out non-English names from a text. (Training dataset includes the set of names that going to use for training)

推荐答案

遗憾的是，该模块计划在未来使用一组自定义实体执行 NER，但目前尚不可用.

Unfortunately, this module's ability to perform NER with a custom set of entities is planned for the future, but not currently available.

如果您熟悉 Python 并愿意付出额外的努力，您可以考虑使用 自然语言工具包(NLTK).Sujit Pal 有一个不错的博文和示例描述使用该包创建自定义 NER 的代码.您可以训练 NLTK NER 模型并将其应用于您感兴趣的数据，从 Azure ML 上的执行 Python 脚本模块中.

If you're familiar with Python and willing to put in the extra footwork, you might consider using the Natural Language Toolkit (NLTK). Sujit Pal has a nice blog post and sample code describing the creation of a custom NER with that package. You may be able to train an NLTK NER model and apply it to your data of interest from within an Execute Python Script module on Azure ML.

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